Category Archives: Statistics

“59% of voters oppose building President Trump’s long-promised wall along the southern border, and only 37% support the measure, according to the Quinnipiac poll.”*

“79% of Americans expect that if a wall is built along the border, the U.S. will ultimately pay for it. Just 14% expect Mexico will pay, as Mr. Trump has claimed. 60% of Republicans, and 91% of Democrats, think the U.S. will pay for the wall if it is built.”*﻿

“The majority of Americans (57%) oppose expanding the construction of walls along the nation’s Southern border, a centerpiece of President Donald Trump’s proposed immigration-related policies.”“83% approve of allowing DACA immigrants to become citizens.”*

“I will take the mantle. I will be the one to shut it down. I’m not going to blame you for it.”—Trump to Nancy Pelosi and Chuck Schumer, December 11th, 2018*

Well, so what? Even a small number of people can really hurt the country, right? So, here’s a study about whether undocumented people increase rates of violent crime:

“[W]e combine newly developed estimates of the unauthorized population with multiple data sources to capture the criminal, socioeconomic, and demographic context of all 50 states and Washington, DC, from 1990 to 2014 to provide the first longitudinal analysis of the macro‐level relationship between undocumented immigration and violence. The results from fixed‐effects regression models reveal that undocumented immigration does not increase violence. Rather, the relationship between undocumented immigration and violent crime is generally negative….”

I always like these stories from The Dodo about sickly animals being nursed back to health by kindly people. As I watch this video, though, I wonder how much meat this person is feeding the dog. My thinking is that it doesn’t make much sense to save one animal if it means that other animals have to die in order to feed it.

How much meat do dogs and cats in the US consume?

If the ~163 million dogs and cats in the US comprised their own country, that country would rank fifth in global meat consumption, behind only Russia, Brazil, the US, and China. Dogs and cats consume 1/4 of the total calories derived from animals in the US.*

But, won’t dogs and cats get very sick if they don’t eat meat regularly?

There have been a handful of studies conducted over the past ~15 years regarding the health of companion dogs and cats fed vegan or vegetarian diets. Although you can find plenty of information from reliable sources around the web about cats being obligate carnivores, every study surveyed has found actual and reported health of dogs and cats fed a wide range of vegan or vegetarian diets to be comparable to the health of pets fed traditional diets. Like humans, dogs and cats probably do not need to eat meat to survive and thrive. (However, cat owners who choose to feed their cats vegan/vegetarian diets may want to monitor the pH of their cats’ urine as some cats may develop health issues on meatless diets.)*

I let my cat go outside freely to exercise its feline extincts. What about me?

While this may be good for the cat in some ways, it’s very harmful to birds and small mammals. Owned cats in the US kill ~765 million birds a year and ~1.38 billion mammals per year.*

1941
Prohibition of Discrimination in the Defense Industry
-Executive Order 8802
-Banned discriminatory employment practices by Federal agencies and all unions and companies engaged in war-related work
-Established the Fair Employment Practices Commission to enforce the new policy
-Signed by FDR

1948
Desegregation of Armed Forces
-Executive Order 9981
-Established the President’s Committee on Equality of Treatment and Opportunity in the Armed Services, committing the government to integrating the segregated military
-Signed by Truman

The Economy

Climate Change

The earth’s climate is extremely important, both economically and biologically. Most Democrats agree with the vast majority of climate scientists that humans have caused all or nearly all of earth’s rapid warming over the past 5-6 decades.* As of 2017, 78% of Democrats agreed that human activity is causing the warming while only 24% of Republicans agree* with the extremely strong scientific consensus.

But, isn’t there still a lot of uncertainty about what’s causing global warming? No. Climate scientists are roughly as certain that humans are causing the rapid warming of the earth’s atmosphere as they are in the basic science of plate tectonics.*

But, is scientific consensus really important? Maybe. One way to look at it is to consider artificial intelligence. Imagine if we looked at research papers of artificial intelligence researchers and polled them and found that 5% of them are warning that there is a high probability of robots taking over the world in the near future. That might be slightly alarming, right? However, if we look at that same information and talk to the same people and find that 97% of those papers and scientists are warning of a robot takeover, governments all over the world would be acting immediately to prevent this.

The first person I talk to comes out guns blazing. I don’t even knock on his door. He just pops out with a “Hey there!”

“Hey, I’m Clif. I’m with the Democrats. I’m collecting signatures for some local candidates.”

“I used to be a Democrat,” he says, “back when they were conservative. Now they’re for the homosexuals and abortion, and they’re against God.”

I say, “Well, you know, I’m not a big fan of abortion, but I think the Democrats have it right. Number one, strangely enough, making more restrictive abortion laws doesn’t actually reduce the rate of abortion.* It’s like Barry Goldwater said: ‘It’s always been around, and it always will be.’* Things we know that help reduce the rate of abortion, though, like increased access to birth control and sex ed are things Democrats are generally for.”*

“Well, that’s true,” he says, “and that’s why I’m not strictly for one side or the other. But, I don’t know why everything has to be gay, gay, gay now. You can’t turn on the TV these days without homosexuals in everything. You know, I believe in the Bible, and the Bible makes it totally clear that homosexuality is wrong. Take Sodom and Gomorrah: God sends angels down to Lot, and the wicked men of the city try to have sex with them. Lot offers them his daughters — now that part’s terrible — but the men want the angels.”

I say, “Yeah, but I would point out that there are different ways to interpret these things. There are people out there who believe — I’m sure — just as strongly in God and the Bible who don’t think homosexuality is bad. In that verse you mentioned, for instance, they might say that God’s problem with the wicked men was not that they were homosexuals but that they wanted to rape strangers. Maybe God is just against people who want to rape other people.”*

He says, “Yeah, there are a lot of people out there who want to distort the truth. They try to call people like me an extremist just because I’ve been married to my wife for 52 years.”

I say, “Well, I wouldn’t call you that. I would just say that I have gay friends myself who I care for a lot. They’re people who I think suffered because they grew up around people who told them that they were bad. They couldn’t change this ‘bad’ thing about themselves, so it made them deeply unhappy. I think that’s terrible.”

He then tells me a bizarre story about a handsome nephew who he says was turned gay by his mom and sisters who would dress him up like a girl, in dresses and makeup. I let that one go. I liked that the guy called his nephew “a real head-turner,” though.

This was like a 20-minute conversation that I won’t recount all of here. It turns out that the guy doesn’t like Jeff Flake because Flake’s nephew apparently … neglected some dogs? The guy doesn’t like McCain because McCain is responsible for the shoddy condition of the VA apparently.

He talks about how you can’t have the Bible in schools anymore, but you can have the “yin yang.” I kinda regret not finding out what the “yin yang” is ….

Trump, though. There’s somethin’ about that Trump guy. He says, “Trump’s a guy who can’t be bought ’cause he’s already a billionaire.”

As I almost always do when I hear Trump’s name, I begin to vomit uncontrollably. No, I’m kidding. I just vomit in my mind. The mind vomit helps to cloud the mental image of Trump.

This ex-Democrat then says, “And the Mueller investigation — the Democrats are just dragging it out. It’s just a waste of taxpayer money.”

I start to say, “Well, the Republicans spent a lot of taxpayer money to investigate Hillary….”

“In conclusion, this article is the first to our knowledge to report that a higher proportion of household gun ownership at the state level is associated with statistically significant increased rates of nonstranger total and firearm homicides. By contrast, we found no robust, statistically significant association between household gun ownership and stranger homicides. Our findings thus challenge the argument that gun ownership deters violent crime, in particular, homicides.”

“Across the nine regions for the early 1990s (n = 9), household handgun ownership rates are positively correlated with the suicide rate (r = 0.59) and are not correlated with either the lifetime prevalence of major depression or suicidal thoughts. After controlling for major depression and suicidal thoughts (and any of the four additional control variables), handgun ownership rates remain significantly associated with the overall suicide rate.”

“Individual-level studies (n=4) are reviewed that investigate the risks and benefits of owning a personal or household firearm. The research suggests that households with firearms are at higher risk for homicide, and there is no net beneficial effect of firearm ownership.

“Two groups of ecological studies are reviewed, those comparing multiple countries and those focused solely on the United States. Results from the cross-sectional international studies (n=7) typically show that in high-income countries with more firearms, both men and women are at higher risk for homicide, particularly firearm homicide.

“Time series (n=10) and cross-sectional studies (n=9) of U.S. cities, states, and regions and for the United States as a whole, generally find a statistically significant gun prevalence–homicide association. None of the studies prove causation, but the available evidence is consistent with the hypothesis that increased gun prevalence increases the homicide rate.”

“Between 1988 and 1997, the suicide, homicide, and unintentional firearm death rates among women were disproportionately higher in states where guns were more prevalent. The elevated rates of violent death in states with more guns was not entirely explained by a state’s poverty or urbanization and was driven primarily by lethal firearm violence, not by lethal nonfirearm violence.”

“Among developed nations, the United States has the highest rate of civilian gun ownership, and the highest homicide rate. We examine whether the United States is merely an exception, or if a relationship between gun availability and homicide exists across all developed nations.

“In simple regressions (no control variables) across 26 high-income nations, there is a strong and statistically significant association between gun availability and homicide rates.

“Conclusion: Across developed countries, where guns are more available, there are more homicides.”

“Positive correlations were obtained between the rates of household gun ownership and the national rates of homicide and suicide as well as the proportions of homicides and suicides committed with a gun.”

“Over the 22 year study period household firearm ownership rates declined across all four regions. In multivariate analyses, each 10% decline in household firearm ownership was associated with significant declines in rates of firearm suicide, 4.2% (95% CI 2.3% to 6.1%) and overall suicide, 2.5% (95% CI 1.4% to 3.6%). Changes in non-firearm suicide were not associated with changes in firearm ownership.

“The magnitude of the association between changes in household firearm ownership and changes in rates of firearm and overall suicide was greatest for children: for each 10% decline in the percentage of households with firearms and children, the rate of firearm suicide among children 0–19 years of age dropped 8.3% (95% CI 6.1% to 10.5%) and the rate of overall suicide dropped 4.1% (2.3% to 5.9%).”

“The US homicide rates were 6.9 times higher than rates in the other high-income countries, driven by firearm homicide rates that were 19.5 times higher. For 15-year olds to 24-year olds, firearm homicide rates in the United States were 42.7 times higher than in the other countries. For US males, firearm homicide rates were 22.0 times higher, and for US females, firearm homicide rates were 11.4 times higher. The US firearm suicide rates were 5.8 times higher than in the other countries, though overall suicide rates were 30% lower. The US unintentional firearm deaths were 5.2 times higher than in the other countries.

“Among these 23 countries, 80% of all firearm deaths occurred in the United States, 86% of women killed by firearms were US women, and 87% of all children aged 0 to 14 killed by firearms were US children.”

“The number of guns per capita per country was a strong and independent predictor of firearm-related death in a given country, whereas the predictive power of the mental illness burden was of borderline significance in a multivariable model. Regardless of exact cause and effect, however, the current study debunks the widely quoted hypothesis that guns make a nation safer.”

“A statistically significant association exists between gun availability and the rates of unintentional firearm deaths, homicides, and suicides. The elevated rates of suicide and homicide among children living in states with more guns is not entirely explained by a state’s poverty, education, or urbanization and is driven by lethal firearm violence, not by lethal nonfirearm violence.”

“Those persons with guns in the home were at greater risk than those without guns in the home of dying from a homicide in the home (adjusted odds ratio = 1.9, 95% confidence interval: 1.1, 3.4). They were also at greater risk of dying from a firearm homicide, but risk varied by age and whether the person was living with others at the time of death.

“The risk of dying from a suicide in the home was greater for males in homes with guns than for males without guns in the home (adjusted odds ratio = 10.4, 95% confidence interval: 5.8, 18.9). Persons with guns in the home were also more likely to have died from suicide committed with a firearm than from one committed by using a different method (adjusted odds ratio = 31.1, 95% confidence interval: 19.5, 49.6).

“Results show that regardless of storage practice, type of gun, or number of firearms in the home, having a gun in the home was associated with an increased risk of firearm homicide and firearm suicide in the home.”

“Among high-income countries, where firearms are more available, more women are homicide victims. Women in the United States are at higher risk of homicide victimization than are women in any other high-income country.”

“As compared with the controls, the victims more often lived alone or rented their residence. Also, case households more commonly contained an illicit-drug user, a person with prior arrests, or someone who had been hit or hurt in a fight in the home. After controlling for these characteristics, we found that keeping a gun in the home was strongly and independently associated with an increased risk of homicide.”

“Although the current study cannot determine causation, firearm mortality in its various forms is most commonly related to the prevalence of firearms and the percent of the population that is African American.”

“We observed a robust correlation between higher levels of gun ownership and higher firearm homicide rates. Although we could not determine causation, we found that states with higher rates of gun ownership had disproportionately large numbers of deaths from firearm-related homicides.”

Do people in red-leaning or blue-leaning states have a bigger carbon footprint?

Just looking at data from the Energy Information Administration from 2014, it looks like red states do produce more CO2 per capita:

I wanted to better quantify this, though, so I ran the data through a Pearson correlation calculator.* Here’s the dataset in case you’d like to check my work:

And, here are the results:

As you can see, mathematically, as the proportion of a state that was Republican or leaned Republican in 2014 went up, so did the state’s per capita CO2 emissions. The value of R is 0.549, a moderate positive correlation. R2: 0.3014.

For the sake of thoroughness, I performed the same calculation for the Democrats. Here’s that dataset:

Here’s the resultant graph:

The value of R is -0.5593, a moderate negative correlation. R2: 0.3128.

How well do states perform economically that have populations leaning Democrat or Republican? To try to answer this question, I took data from Gallup for 2016* to determine political leaning and compared it to data from the US Bureau of Economic Analysis for state per capita GPD* using a Pearson correlation calculation.*

State Per Capita GDP vs Percent of States Identifying as Democrat or Lean Democrat

From the resulting graph, one might expect a slight positive correlation, and one would be right. The value of R is 0.462. Although technically a positive correlation, the relationship between the variables is weak. The value of R2, the coefficient of determination, is 0.2134.

* * *

For the sake of thoroughness, we can perform the same test for percentage of states that lean Republican:

State Per Capita GDP vs Percent of States Identifying as Rep or Lean Rep

From the resulting graph, one might expect a slight negative correlation, and this is what we find. The value of R is -0.4692. Although technically a negative correlation, the relationship between the variables is weak. The value of R2, the coefficient of determination, is 0.2201.

* * *

What, if anything does this prove? Primarily, it doesn’t appear that either Republicans or Democrats can strongly boast of improving the economy if that metric is based on per capita income. However, if one side did want to make the claim to being better for the economy, the analysis appears to support the Democrats. These results are similar to those I found in another Pearson correlation I performed using Gallup data in comparison to unemployment figures.

So, here’s a question: Do Republican states do better or worse than Democratic states with respect to unemployment? CNN looked into this a bit here. They just looked at states with Republican or Democratic governors, though. There, they found about a 1 percentage point difference in unemployment in favor of Republicans. I’m not sure, though, that the state governor is the best gauge.

My little study here assumes that party preference correlates closely with party dominance in each state. Am I correct in assuming this? I don’t know. Would a more responsible researcher have figured this out before publishing this? Yeah. Am I feeling like I don’t care enough at the moment? Yeah.

With this auspicious intro, the results:

The party affiliation is self-identified from Gallup; the unemployment figures are from the BLS.

Here’s what the two datasets look like plotted:

Just looking at that mess, there doesn’t appear to be any correlation. This graph was generated at Social Science Statistics. Their analysis goes like this:

The value of R is -0.2407. Although technically a negative correlation, the relationship between your variables is only weak(nb. the nearer the value is to zero, the weaker the relationship).

The value of R2, the coefficient of determination, is 0.0579.

Here are the data in case you like to look at such things:

For the sake of thoroughness, we can do the same test for Democrats. Here’s the plot for that:

As you can see, it’s still a mess. You can sort of maybe see that there’s the slightest positive correlation, but I wouldn’t expect that to be a statistically significant correlation. I do like that, if you look at it just right, it looks a little like a hummingbird.

Here’s the Pearson correlation analysis:

The value of R is 0.2249. Although technically a positive correlation, the relationship between your variables is weak (nb. the nearer the value is to zero, the weaker the relationship).